Hiflylabs Case Study

MOL Group is one of the leading integrated oil and gas corporations in Europe, with operations spanning the entire energy value chain—petrochemicals, refining, exploration, production, and marketing. They boast more than 85 years of experience and production activity in 8 countries. Their diverse portfolio consists not only of oil and gas, but also sustainability initiatives, urban mobility, and distribution chains. In 2018, Hiflylabs developed a location-based pricing scheme to support MOL in meeting their retail ambitions.

3.87%

gross margin growth with retail pricing & assortment optimization.

9.54%

revenue increase across top performers.

Challenge

MOL gas stations are present in multiple locations across Europe, also offering a selection of retail goods at gas station convenience stores. These stores face a wide variety of local competitive environments, and a need for dynamic optimization in their pricing strategy became apparent. The challenge was to define the optimal pricing level for each location to generate the highest margin on convenience articles.

Solution

Hiflylabs deployed its retail pricing methodology to improve the client's non-fuel pricing scheme. This methodology was based on calculating price elasticities for each location, and taking into account the business hypotheses of the client's experts.

The output was an article-level price recommendation & assortment optimization system. After a 6 month BAU period, the tested locations yielded an average of 3.87% gross margin growth above the control group, with a 9.54% increase across the top performers.

Service

AI

Industries

Energy

Technologies

R

MS SQL

Technologies

R

MS SQL

Hiflylabs solved a location-based retail pricing problem. We’ve been working together on data-driven challenges ever since.István Mag
- Head of Digital Factory, MOL Group

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Petrol retailer optimizes non-fuel pricing

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